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distributed average tracking Problem Under Directed Networks: A distributed Estimator-Based Design

IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2022年第2期9卷 930-942页

作者： Yu, Changbin Wang, He Yu, Wenwu Shandong First Med Univ & Shandong Acad Med Sci Coll Artificial Intelligence & Big Data Med Sci Jinan 250021 Peoples R China Fudan Univ Inst Intelligent Robots Shanghai 200433 Peoples R China Southeast Univ Sch Math Nanjing 210096 Peoples R China

This article considers the distributed average tracking (DAT) problem that a group of agents aims to track the average of local reference signals. The communication network is strongly connected but not required to be weight balanced. A framework of distributed estimator-based algorithm design without any initialization requirement is presented. For agents with nominal first-order (FO) dynamics, a class of distributed estimators is proposed to estimate the average of local reference signals within fixed time, with which each agent finally achieves the DAT within fixed time. For agents with second-order dynamics subject to modeling uncertainty, unmodeled dynamics, as well as external disturbances, a class of distributed estimator is proposed to estimate the average of local reference signals within fixed time, and then a local disturbance-observer-based control protocol is proposed for each agent to achieve DAT asymptotically. Different from most of the existing DAT results under general directed networks that DAT error can only be made globally ultimately bounded, the exact DAT can be achieved within fixed time or asymptotically here. Further, the idea of distributed estimator is applied to solve a class of distributed optimization problems within finite time. Finally, two simulation examples are given to show the effectiveness of the theoretical results.

关键词： Directed network distributed average tracking distributed optimization finite-time convergence uncertainty

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Observer-based distributed average tracking of second-order multi-agent systems with disturbances

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL 2024年第5期34卷 3408-3424页

作者： Liu, Boning Wei, Bo Yin, Huan North China Elect Power Univ Sch Control & Comp Engn Beijing Peoples R China North China Elect Power Univ Sch Math & Phys Beijing 102206 Peoples R China

This article addresses the problem of distributed average tracking for second-order multi-agent systems with disturbances. The unknown disturbances inject into the velocity dynamics, resulting in the degradation of system stability. An extended state observer is designed to estimate the velocities and disturbances. Then, an observer-based average tracking protocol is proposed, which does not require velocity measurements, and the unknown disturbances are compensated by the estimations. The protocol is implemented in a distributed fashion, without requiring any global information, and is robust to initialization errors. Through Lyapunov analysis, it is verified that the second-order multi-agent system can achieve distributed average tracking under the proposed protocol. Finally, the effectiveness of the control method is demonstrated by simulations.

关键词： distributed average tracking disturbances extended state observer multi-agent systems

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An active queue management method for multiple bottleneck networks based on distributed average tracking

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JOURNAL OF CONTROL AND DECISION 2024年

作者： Huang, Bomin Cui, Qingfu Zou, Yao Jimei Univ Coll Comp Engn Xiamen 361021 Peoples R China Northeastern Univ Qinhuangdao Sch Control Engn Qinhuangdao Peoples R China Univ Sci & Technol Beijing Sch Intelligence Sci & Technol Beijing Peoples R China

The active queue management (AQM) is a key technology for the information infrastructure and the Internet. The AQM for multiple bottleneck networks is especially challenging than that for single-bottleneck networks because the stability analysis of multiple bottleneck networks is more complex. In this paper, the active queue management problem for multiple bottleneck networks is considered. A novel random early detection algorithm is designed based on distributed average tracking technology, which is used to estimate the global queue length and improve the network's performance. Sufficient conditions for global asymptotic stability of the closed-loop active queue management system are presented, and some simulation results with NS-2 are given. Compared with the RED algorithm, simulation results show that the presented algorithm has smaller oscillations at routers, which highlights its effectiveness.

关键词： distributed algorithm distributed average tracking multiple bottleneck network active queue management

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distributed average tracking control for a class of unknown heterogeneous nonlinear second-order multiagent systems with external disturbances

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NONLINEAR DYNAMICS 2025年

作者： Yao, Dingchao Xu, Bowen Yu, Dengxiu Li, Xiaoyu Wang, Zhen Northwestern Polytech Univ Sch Cybersecur Xian 710072 Peoples R China Northwestern Polytech Univ Sch Artificial Intelligence Opt & Elect Xian 710072 Peoples R China

In this paper, the distributed average tracking control problem is addressed for a class of unknown heterogeneous nonlinear second-order multiagent systems subjected to the external disturbances. Under local interaction constraints where each agent accesses only its neighborhood information, a distributed estimator with a smooth operator is proposed for each agent to estimate the average value of all reference signals, ensuring stable tracking while eliminating chattering phenomena. Additionally, due to the system uncertainties and external disturbances, it is challenging to acquire an accurate system model and design corresponding control algorithm, hindering the closed-loop stability analysis. To address this challenge, an approximation module assisted by a radial basis function neural network and a disturbance observer are integrated into an adaptive control algorithm, ensuring that each agent can track the averaged reference signals. Moreover, the stability of the proposed control algorithm is rigorously proven through Lyapunov-based theoretical analysis. Finally, a numerical example is presented to validate the feasibility of the proposed algorithm.

关键词： distributed average tracking Adaptive control distributed estimation Heterogeneous multiagent systems

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Finite-Time distributed average tracking for Multiagent Optimization With Bounded Inputs

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2023年第8期68卷 4948-4955页

作者： Shi, Xinli Wen, Guanghui Cao, Jinde Yu, Xinghuo Southeast Univ Sch Cyber Sci & Engn Nanjing 210096 Peoples R China Southeast Univ Sch Math Jiangsu Prov Key Lab Networked Collect Intelligenc Nanjing 210096 Peoples R China RMIT Univ Sch Engn Melbourne Vic 3001 Australia

In distributed optimization (DO), the designed algorithms are expected to have a fast convergence rate but less computation cost. Moreover, the boundedness of the control inputs is generally required for practical networking agent systems with actuator limitations. Motivated by these observations, we first revisit the well-known finite-time distributed average tracking (FTDAT) problem where a novel sufficient condition on the control gain and the finite settling time estimation are derived based on the minimum cut of the underlying topology. Then, based on FTDAT, three types of discontinuous dynamics with bounded inputs are designed for solving unconstrained and constrained DO problems, respectively. The first algorithm can successfully find the optimal solution for an unconstrained DO in finite time. For DO problems with a common constraint set or separated equality constraints, two projection-based algorithms are designed and utilized to first make the agents' states achieve consensus in finite time, and then drive the common state to the optimum exponentially. Finally, several case studies and extensive numerical simulations are conducted to testify the designed algorithms.

关键词： Index Terms-Bounded input distributed average tracking finite-time consensus multiagent optimization

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distributed average tracking in Weight-Unbalanced Directed Networks

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2021年第9期66卷 4436-4443页

作者： Sun, Shan Chen, Fei Ren, Wei Univ Calif Riverside Dept Elect & Comp Engn Riverside CA 92521 USA Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang 110004 Peoples R China Northeastern Univ Qinhuangdao Sch Control Engn Qinhuangdao 066004 Hebei Peoples R China

This article studies a distributed average tracking (DAT) problem, in which a collection of agents work collaboratively, subject to local communication, to track the average of a set of reference signals, each of which is available to a single agent. Our primary objective is to seek a design methodology for DAT under possibly weight-unbalanced directed networks-the most general and thus most challenging case from the network topology perspective, which has few results in the literature. For this purpose, we propose a distributed algorithm based on a chain of two integrators that are coupled with a distributed estimator. It is found that the convergence depends on not only the network topology but also the deviations among the reference signal accelerations. Another primary interest of this article stems from the dynamics perspective-a point perceived as a main source of control design difficulty for multiagent systems. Indeed, we devise a nonlinear algorithm that is capable of achieving DAT under weight-unbalanced directed networks for agents subject to high-order integrator dynamics. The results show that the convergence to the vicinity of the average of the reference signals is guaranteed as long as the signals' states and control inputs are all bounded. Both algorithms are robust to initialization errors, i.e., DAT is insured even if the agents are not correctly initialized, enabling the potential applications in a wider spectrum of application domains.

关键词： Heuristic algorithms Directed graphs Laplace equations Eigenvalues and eigenfunctions distributed algorithms Convergence Network topology distributed average tracking multiagent system weight-unbalanced directed graphs

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distributed average tracking for Linear Heterogeneous Multi-Agent Systems With External Disturbances

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IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING 2021年第4期8卷 3491-3500页

作者： Wu, Yanzhi Liu, Lu City Univ Hong Kong Dept Biomed Engn Kowloon Hong Kong Peoples R China Beijing Adv Innovat Ctr Intelligent Robots & Syst Beijing 100081 Peoples R China

In this paper, we address the distributed average tracking (DAT) problem for linear multi-agent systems with heterogeneous dynamics and external disturbances. The objective is that each agent can accurately track the desired tracking signal by designing controllers without initialization. The desired tracking signal means the average of individual time-varying reference inputs (one per agent). The current problem setting is technically more challenging and more practical than existing works. Based on the feedforward method, a state feedback controller is first designed to solve the DAT problem, which can guarantee the exponential convergence of tracking errors in the case where the desired tracking signal and external disturbances are known. Then the DAT problem for linear heterogeneous multi-agent systems with unknown desired tracking signal and unknown external disturbances is also solved. A distributed observer is designed for each agent to estimate the desired tracking signal. In parallel, the output of each agent is driven to track the output of the observer. Since each agent cannot access the desired tracking signal and external disturbances, a dynamic compensator independent of the exogenous signal and a dynamic internal-model based component are introduced to overcome these challenges. Finally, a numerical example is included for illustration.

关键词： Multi-agent systems Heuristic algorithms Steady-state Vehicle dynamics Regulators Laplace equations Eigenvalues and eigenfunctions distributed average tracking heterogeneous multi-agent systems distributed control

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Robust distributed average tracking for Double-Integrator Agents Without Velocity Measurements Under Event-Triggered Communication

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IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS 2021年第2期8卷 828-837页

作者： Ding, Yong Ren, Wei Zhao, Yu Univ Calif Riverside Dept Elect & Comp Engn Riverside CA 92521 USA Northwestern Polytech Univ Sch Automat Xian 710129 Peoples R China

This article focuses on an event-triggered mechanism to solve the distributed average tracking problem for double-integrator agents without velocity measurements. In some practical applications, velocity measurements may be unavailable due to technology and space limitations, and it is also usually less accurate and more expensive to implement. Before deriving the event-triggered approach, we first present a base algorithm without using velocity measurements, which sets the stage for the development of the event-triggered algorithm. The base algorithm has an advantage over the existing related works in the sense that there is no global information requirement for parameter design. Building on the base algorithm, we present an event-triggered algorithm that further removes the continuous communication requirement and is free of Zeno behavior. It is suitable for practical implementation, since in reality, the bandwidth of the communication network and power capacity are usually constrained. The event-triggered algorithm overcomes some practical limitations, such as the unbounded growth of the adaptive gain and requirement of additional internal dynamics, by constructing a new triggering strategy. In addition, a continuous nonlinear function is used to approximate the signum function to reduce the chattering phenomenon in reality. Numerical simulations are provided to illustrate the obtained results.

关键词： distributed average tracking double-integrator agents event-triggered communication velocity measurements

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Adaptive Resilient distributed average tracking of Multiagent Systems

Adaptive Resilient Distributed Average Tracking of Multiagen...

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第43届中国控制会议

作者： Chenyu Ji Haotian Wang Fei Chen School of Control Engineering Northeastern University at Qinhuangdao College of Information Science and Engineering Northeastern University College of Artificial Intelligence Nankai University

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

This paper tackles the problem of achieving distributed average tracking in a multi-agent system in the presence of network attacks. Traditionally, controllers are designed using Laplacian matrix eigenvalues, but practical limitations of obtaining global information necessitate a fully distributed design. This study relies solely on agents' local information from their neighbors, introducing adaptive parameters to develop the adaptive resilient distributed average tracking method. This fully distributed method aims to enable distributed average tracking among agents within an undirected graph, even when faced with bounded attacks. Theoretical findings are validated through simulation examples.

关键词： Adaptive control Multi-agent systems distributed average tracking Undirected graphs

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distributed average tracking of Physical Second-Order Agents With Heterogeneous Unknown Nonlinear Dynamics Without Constraint on Input Signals

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第3期64卷 1178-1184页

作者： Ghapani, Sheida Rahili, Salar Ren, Wei Univ Calif Riverside Dept Elect & Comp Engn Riverside CA 92521 USA

This paper addresses distributed average tracking of physical second-order agents with heterogeneous unknown nonlinear dynamics, where there is no constraint on input signals and there is no need for correct initialization. The unknown non-linear terms in agents' dynamics are heterogeneous, satisfying a Lipschitz-like condition that will be defined later and is more general than the Lipschitz condition. In the proposed algorithm, a control input and a filter are designed for each agent. Each agent's filter has two outputs and the idea is that the first output estimates the average of the input signals, and the second output estimates the average of the input velocities asymptotically. In parallel, each agent's position and velocity are driven to track, respectively, the first and the second outputs. Having an unknown term in agents' dynamics necessitates designing the filters for agents. Since the nonlinear terms in agents' dynamics can be unbounded and the input signals are arbitrary, novel time-varying gains are employed in agents' filters and control inputs to overcome these unboundedness effects. Finally, the results are improved to achieve the distributed average tracking for a group of double-integrator agents, where there is no constraint on input signals and the filter is not required anymore. Numerical simulations are also presented to illustrate the theoretical results.

关键词： Cooperative control distributed average tracking distributed control multiagent systems

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